• 제어로봇시스템학회논문지
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• 제8권6호
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• pp.468-476
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• 2002

The confidence of information from image processing depends on the original image quality. Enhancing the confidence by an algorithm has an essential limitation. Especially, road images are exposed to lots of noisy sources, which makes image processing difficult. We, in this paper, propose a FNN (fuzzy-neural network) capable oi deciding the quality of a road image prior to extracting lane-related information. According to the decision by the FNN, road images are classified into good or bad to extract lane-related information. A CDF (cumulative distribution function), a function of edge histogram, is utilized to construct input parameters of the FNN, it is based on the fact that the shape of the CDF and the image quality has large correlation. Input pattern vector to the FNN consists of ten parameters in which nine parameters are from the CDF and the other one is from intensity distribution of raw image. Correlation analysis shows that each parameter represents the image quality well. According to the experimental results, the proposed FNN system was quite successful. We carried out simulations with real images taken by various lighting and weather conditions and achieved about 99% successful decision-making.

• 대한원격탐사학회지
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• 제39권4호
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• pp.395-407
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• 2023

Super-resolution (SR) has great significance in image processing because it enables downstream vision tasks with high spatial resolution. Recently, SR studies have adopted deep learning networks and achieved remarkable SR performance compared to conventional example-based methods. Deep-learning-based SR models generally require low-resolution (LR) images and the corresponding high-resolution (HR) images as training dataset. Due to the difficulties in obtaining real-world LR-HR datasets, most SR models have used only HR images and generated LR images with predefined degradation such as bicubic downsampling. However, SR models trained on simple image degradation do not reflect the properties of the images and often result in deteriorated SR qualities when applied to real-world images. In this study, we propose an image degradation model for HR satellite images based on the modulation transfer function (MTF) of an imaging sensor. Because the proposed method determines the image degradation based on the sensor properties, it is more suitable for training SR models on remote sensing images. Experimental results on HR satellite image datasets demonstrated the effectiveness of applying MTF-based filters to construct a more realistic LR-HR training dataset.

• 한국정보통신학회논문지
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• 제14권1호
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• pp.225-232
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• 2010

용접부 내에 존재하는 결함의 형태, 위치, 크기 등의 정보를 정량적으로 파악하기 위하여 초음파 탐상 검사가 많이 활용되는데, 최근 들어 용접부의 결함 탐상을 위해, 검사과정을 기계적 스캐너로 자동화한 자동 초음파 탐상 시스템이 많은 산업 분야에서 활용되고 있고, 특히 배관 용접부의 건전성 평가를 위한 비파괴안전진단에서 그 활용 폭이 커지고 있다. 본 논문에서는 배관 용접부의 자동 초음파 검사를 위한 알고리즘 구현과 결함 영상을 보정하여 주는 결함영상 처리 시스템을 설계 및 구현하였다. 적용된 기법으로는 초음파 A-Scan 압축 알고리즘, Synthetic Aperture Focusing 알고리즘, 결함영상증폭 알고리즘과 이와 관련된 소프트웨어 설계 및 구현에 대하여 논한다.

• 로봇학회논문지
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• 제13권1호
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• pp.8-15
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• 2018

This paper proposes a convolutional neural network model for distinguishing areas occupied by obstacles from a LiDAR image converted from a 3D point cloud. The channels of a LiDAR image used as input consist of the distances to 3D points, the reflectivities of 3D points, and the heights of 3D points from the ground. The proposed model uses a LiDAR image as an input and outputs a result of a segmented LiDAR image. The proposed model adopts refinement modules with skip connections to segment a LiDAR image. The refinement modules with skip connections in the proposed model make it possible to construct a complex structure with a small number of parameters than a convolutional neural network model with a linear structure. Using the proposed model, it is possible to distinguish areas in a LiDAR image occupied by obstacles such as vehicles, pedestrians, and bicyclists. The proposed model can be applied to recognize surrounding obstacles and to search for safe paths.

• 스마트미디어저널
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• 제5권1호
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• pp.49-54
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• 2016

Medical image processing is a compulsory process to diagnose many kinds of disease. Therefore, an automatic algorithm for this task is highly demanded as an important part to construct a computer-aided diagnosis system. In this paper, we introduce an automatic method to segment the liver region from 3D abdominal CT images using Otsu method. First, we choose a 2D slice which has most liver information from the whole 3D image. Secondly, on the chosen slice, we enhanced the image based on its intensity using Otsu method with multiple thresholds and use the threshold to enhance the whole 3D image. Then, we apply a liver mask to mark the candidate liver region. After that, we execute the Otsu method again to segment the liver region from the chosen slice and propagate the result to the whole 3D image. Finally, we apply preprocessing on the frontal side of 3D images to crop only the liver region from the image.

• Journal of Astronomy and Space Sciences
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• 제27권4호
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• pp.309-318
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• 2010

We introduce a technical approach for reducing three-dimensional infrared (IR) spectroscopic data generated by integral field spectroscopy or slit-scanning observations. The first part of data reduction using IRAF presents a guideline for processing spectral images from long-slit IR spectroscopy. Multichannel image reconstruction, Image Analysis and Display (MIRIAD) is used in the later part to construct and analyze the data cubes which contain spatial and kinematic information of the objects. This technic has been applied to a sample data set of diffuse 2.1218 ${\mu}m$ $H_2$ 1-0 S(1) emission features observed by slit-scanning around Sgr A East in the Galactic center. Details of image processing for the high-dispersion infrared data are described to suggest a sequence of contamination cleaning and distortion correction. Practical solutions for handling data cubes are presented for survey observations with various configurations of slit positioning.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.61-63
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• 2005

Retreiving indoor scene reference image from database using visual information is important issue in Robot Navigation. Scene matching problem in navigation robot is not easy because input image that is taken in navigation process is affinly distorted. We represent probabilistic framework for the feature matching between features in input image and features in database reference images to guarantee robust scene matching efficiency. By reconstructing probabilistic scene matching framework we get a higher precision than the existing feaure-feature matching scheme. To construct probabilistic framework we represent each image as Gaussian Mixture Model using Expectation Maximization algorithm using SIFT(Scale Invariant Feature Transform).

• 전자공학회논문지B
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• 제30B권5호
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• pp.90-102
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• 1993

In this paper, we propose a prgressive image transmission technique using hierarchical pyramid data structure which is constructed based on the projection data of an image. To construct hierarchical Gaussian pyramids, we first divide an image into 4$\times$4 subblocks and generate the projection data of each block along the horizontal, vertical, diagonal, and antidiagonal directions. Among images reconstructed by backprojecting the projection data along a single direction, the one giving the minimum distortion is selected. The Gaussian pyramid is recursively generated by the proposed algorithm and the proposed Gaussian images are shown to preserve edge information well. Also, based on the projection concept a new transmission scheme of the lowest Laplacian plane is presented. Computer simulation shows that the quantitative performance of the proposed pyramid coding technique using projection concept is similar to those of the conventional methods with transmission rate reduced by 0.1 ~ 0.2 bpp and its subjective performance is shown to be better due to the edge preserving property of a projection operation.

• 아동학회지
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• 제25권6호
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• pp.53-68
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• 2004

The purpose of this study was to develop an instrument for adolescent's image about their father. The preliminary survey was performed for 318 adolescents in Seoul. It was a free-writing style survey for adolescent's image, feeling, and thoughts about their father. The main survey which included 121 contents were performed for 400 students in Seoul and finally 75 contents were selected by the results of factor analysis and contents validation. The contents were categorized into 10 sub-variables based on previous studies. 10 sub-variables are Father of mature character, Father who do love me, Father who is devoted to his parents, Father as a friend, Father as a counsellor, Father who is very domestic, Father who is exhausted with work, Father who is hard to be familiar for me, Father with financial competence, Father responsible for supporting the family. This study showed construct validity and concurrent evidence because the correlation among the sub-variables and total score were high.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 1999년도 추계종합학술대회
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• pp.239-243
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• 1999

모자이크 영상은 중복되어지는 객체와 배경에 대한 2차원 영상의 정보를 가진다. 본 연구에서 모자이크 영상의 정보생성 방법에 대하여 설명한다. 이를 기초로 지정된 장소의 3차원 형상을 추정, 카메라 앵글을 2차원 영상이 가지는 시점에서 3차원의 새로운 시점으로 바꾸는 효율적인 애니메이션 방법에 대해 제안한다.